Commercial

Swimsuit Human Segmentation Dataset

The dataset consists of RGB images of people in swimsuits with corresponding segmentation masks and detailed annotations, designed for semantic segmentation, body-part segmentation, and pose estimation tasks in deep learning, computer vision, and object detection models.

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  • images
    14,358
  • people
    7,179
  • Segmentation
  • Computer Vision
  • Machine Learning
  • Object Detection
  • Pose Estimation
  • images
    14,358
  • people
    7,179

Dataset Info

Characteristic Data
Description Image of people for facial recognition
Data types Image
Tasks Human Segmentation, Pose Estimation, Computer Vision
Number of people 7,179
Number of files in a set 2 (image + mask)
Total number of files 14,358
Labeling Metadata (ID, gender, body frame, tattoos(boolean), mirror photo(boolean ))
Gender Male, Female
Types of body frames Normal, athletic, overweight

Statistics

Distribution by gender

Technical
Characteristics

Characteristic Data
Image extension jpg
Image resolutions Min = 327x555, max = 3840x5760
Mask extension png
Mask resolutions Min = 327x555, max = 3840x5760
Source and collection methodology: Data was collected via crowdsourcing platforms.

Dataset Use Cases

  • Fashion & Apparel

    Training Clothing Recognition Models

    Swimsuit Human Segmentation Dataset is valuable for building clothing datasets and people clothing segmentation models. With detailed segmentation masks of swimwear, researchers can train vision models for apparel recognition, body segmentation, and pose estimation. Such datasets help improve product tagging, catalog automation, and style-based search in fashion platforms.



  • Computer Vision & AI Research

    Improving Human Parsing and Body Part Segmentation

    This human segmentation dataset supports semantic segmentation and instance segmentation tasks. The dataset consists of RGB images of people in swimsuits, paired with manual annotations for accurate body-part segmentation. Researchers can use it for deep learning experiments, neural network training, and evaluating segmentation accuracy across different body shapes and human poses.



  • Healthcare & Sports Science

    Modeling Human Body Shapes for Analysis

    Sports scientists and healthcare researchers use the body part segmentation datasets to study human body proportions and movement. The detailed annotations allow precise analysis of body parts, which supports pose estimation and training vision models for motion tracking, rehabilitation studies, and performance optimization in athletics and swimming research.



  • Robotics & Smart Devices

    Enhancing Human Detection and Interaction Systems

    Robotics and AR/VR developers apply this dataset for training object detection and human parsing algorithms. The training data includes manually segmented images, enabling robots and smart devices to achieve more accurate recognition of human poses. This large-scale dataset significantly improves computer vision applications in interactive environments.



FAQs

What is included in Swimsuit Human Segmentation Dataset?
The dataset includes 14,358 files, consisting of RGB images of 7,179 people and their corresponding segmentation masks. Each file pair provides both the original image and the manually segmented mask, making it a strong training set for vision tasks.
What types of annotations are provided?
The dataset offers metadata annotations such as ID, gender, body frame type, tattoos (boolean), and mirror photo (boolean). In addition, it provides binary segmentation masks for each human body, supporting body part segmentation dataset research and neural network training.
Is it possible to request a custom dataset?
Yes, Unidata can create custom datasets tailored to your requirements. You may request additional human poses, body-part segmentation, or specialized annotations to train vision models with higher segmentation accuracy and more detailed annotations.
What can Swimsuit Human Segmentation Dataset be used for?
The dataset can be used for semantic segmentation, instance segmentation, and pose estimation tasks. It supports research and development in object detection, human parsing, automatic segmentation, and deep learning models that require precise human body segmentation dataset inputs.
How long does it take to receive the dataset?
It typically takes 3–10 days to receive the dataset. Once you submit a request, we will contact you to review the details and finalize the necessary documents. After signing and payment, Swimsuit Human Segmentation Dataset will be securely delivered within this timeframe.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. All datasets are designed in line with GDPR compliance and other data protection frameworks. Data is collected responsibly from lawful sources.
How is the data stored?
Unidata ensures all datasets are stored safely on AWS infrastructure, built for security, availability, and scalability. Our operations comply with ISO 27001 and ISO 27701, aligning with international benchmarks for data security and privacy. This delivers a trusted, compliant, and privacy-focused environment for users.
Still have questions about using Unidata datasets? Read our user-guides

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